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20172021
most citedA tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint

75 citations · 133 across the 3 of their papers we have counts for

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5 papers · 1 filter

stat.ME202175 cited

A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint

J Hoogland, J IntHout, M Belias +6

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions…

stat.ME20208 cited

A regression-based method for detecting publication bias in multivariate meta-analysis

Chuan Hong, Jing Zhang, Yang Li +3

Publication bias occurs when the publication of research results depends not only on the quality of the research but also on its nature and direction. The consequence is that publi…

stat.ME2020

Clinical Prediction Models to Predict the Risk of Multiple Binary Outcomes: a comparison of approaches

Glen P. Martin, Matthew Sperrin, Kym I. E. Snell +2

Clinical prediction models (CPMs) are used to predict clinically relevant outcomes or events. Typically, prognostic CPMs are derived to predict the risk of a single future outcome.…

stat.ME2018

Testing small study effects in multivariate meta-analysis

Chuan Hong, Georgia Salanti, Sally Morton +4

Small study effects occur when smaller studies show different, often larger, treatment effects than large ones, which may threaten the validity of systematic reviews and meta-analy…

stat.ME201750 cited

A matrix-based method of moments for fitting multivariate network meta-analysis models with multiple outcomes and random inconsistency effects

Dan Jackson, Sylwia Bujkiewicz, Martin Law +2

Random-effects meta-analyses are very commonly used in medical statistics. Recent methodological developments include multivariate (multiple outcomes) and network (multiple treatme…